test_that("fit_power_law() works", {
  # g <- sample_pa(100) # increase this number to have a better estimate
  # d <- degree(g, mode = "in")
  d <- c(
    9, 3, 8, 1, 10, 4, 8, 0, 4, 4, 5, 2, 2, 7, 2, 0, 0, 0, 1, 0, 5, 0, 1, 2, 0, 0,
    1, 3, 0, 1, 1, 0, 0, 0, 0, 2, 1, 0, 0, 0, 1, 0, 0, 1, 0, 0, 1, 0, 1, 1, 0, 0,
    0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0,
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0
  )

  expected <- list(
    continuous = FALSE,
    alpha = 1.9113310272735056,
    xmin = 1,
    logLik = -65.06453615610745,
    KS.stat = 0.07720553650317852
  )
  fit <- fit_power_law(d)

  expect_equal(fit, expected)

  set.seed(20241017)
  expected_p <- 0.2308
  fit <- fit_power_law(d, p.value = TRUE)

  expect_equal(fit[names(fit) != "KS.p"], expected)
  expect_equal(fit$KS.p, expected_p, tolerance = 1e-2)
})